Blind Matching Filtering Algorithm for Spectrum Sensing under Multi-Path Channel Environment

Matching filtering has been proven to be the optimal spectrum sensing algorithm under Gaussian white noise. However, application of this is limited because its dependence on prior information. In paper, we propose a based blind matching (BMF) by using correlation between adjacent received signals dispersive channels. Theoretical analysis shows that proposed can achieve performance comparable without requiring information primary user. Thus, superior detection performance. Moreover, an improved BMF (IBMF) basis different time-delay signals. IBMF utilizes more comprehensive and achieves better compared BMF. Furthermore, two algorithms have lower computational complexity than classical approaches covariance matrix Numerical simulations confirm detectors validate theoretical analysis.